Optimization of Courier Delivery Route among Hubs in Johor by Using Mixed Integer Programming, Genetic Algorithm and Ant Colony Optimization

The quick growth of e-commerce has significantly increased demand for courier services, creating pressure on logistics infrastructure to manage delivery operations efficiently. This study focuses on the optimization of courier delivery routes for GDex Express to determine the optimal delivery route based on distance and time travelled among hubs in Johor. Mixed Integer Programming, Genetic Algorithm, and Ant Colony Optimization were proposed in this study in order to solve the travelling salesman problem (TSP) by using Python software. This study mainly focuses on 13 GDex Express delivery hubs in Johor with the data based on total distance travelled and average time travelled that selected into three different time periods at 8.00 a.m., 1.00 p.m. and 6.00 p.m. for weekdays and weekends. There are two optimal delivery routes generated respectively in terms of total distance travelled and average time travelled. The results shows that Mixed Integer Programming provided optimal solution as benchmarking, while Genetic Algorithm outperformed Ant Colony Optimization in comparing which algorithm is more closer to the optimal solution. Thus, this study provides solutions to the GDex Express in order to improving the delivery effectiveness and reducing the operating costs by reducing the travel time and distance.

Courier services, GDex Express, Optimization, Mixed Integer Programming, Genetic Algorithm

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